Engineers at MIT (Massachusetts Institute of Technology) have developed a technique for forecasting technological advancement. Researchers determined the improvement rates of 28 different technologies, including solar photovoltaic, 3-D printing, fuel-cell technology, and genome sequencing. The work began by scanning approximately 500,000 technology-related patents using a method for selecting patents relevant to each technology. By analysing metrics of patents in each domain, the researchers found that certain forward citations predict technological growth more reliably than others. An equation devised from those metrics was then applied to determine the rate of improvement for 28 technologies. The researchers described the method as significantly less laborious than most traditional forecasting techniques.<\/p>\n
Benson and Chris Magee, Professors of the Practice of Engineering Systems at MIT, published their results in the journal PLoS ONE<\/em>. The paper presents fundamental findings and equations relating technological improvement to a variety of patent characteristics. Magee had been working on the forecasting method since 2003, seeking to determine the rate of technological growth by comparing data with Moore’s Law. In 2010, he identified the US patent record as a significant resource for technology data and resolved to use it. By 2012, Magee and Benson had developed a method for identifying relevant patent sets by selecting patents that overlap between the US and international patent-classification systems.<\/p>\n The method allowed the team to repeatedly identify the same set of patents representing a given technology within hours rather than months. From these relevant patent sets, researchers identified metrics indicating a technology’s rate of improvement. Average forward citations within the first three years after publication, and average date of publication, were the metrics found to predict technological improvement. The team then used this approach to predict the improvement rates of 11 emerging technologies over the next 10 years. According to their results, the fastest-growing domains appear to be online learning and digital representation, while slower-progressing technologies include food engineering and nuclear fusion.<\/p>\n Magee expressed the hope that the method might be used like a rating system, comparable to Standard & Poor’s and other stock-market indices. Benson observed:<\/p>\n We can help reduce the uncertainty of the capabilities of a technology in the future, not to zero, but to a more manageable number. I believe that’s valuable in a lot of different ways.<\/p><\/blockquote>\n The method is expected to be of use to any organisation willing to invest in technology, particularly government agencies and firms operating in the technology sector.<\/p>\n This article is for general information and does not constitute legal advice. Readers should consult a qualified attorney before acting on any matter discussed here.<\/p>\n","protected":false},"excerpt":{"rendered":" MIT researchers have introduced a patent-based method for forecasting technological growth, focusing on citation metrics and classification system overlaps. Their approach provides organisations with a structured, less labor-intensive technique to predict technology improvement rates and reduce investment uncertainty.<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"iawp_total_views":37,"footnotes":""},"categories":[14],"tags":[6573,7125,7126,3023,7127,193,7124],"class_list":["post-21433","post","type-post","status-publish","format-standard","hentry","category-patents","tag-emerging-technologies","tag-innovation-metrics","tag-mit-research","tag-patent-analysis","tag-patent-citations","tag-technological-growth","tag-technology-forecasting"],"_links":{"self":[{"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/posts\/21433","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/comments?post=21433"}],"version-history":[{"count":4,"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/posts\/21433\/revisions"}],"predecessor-version":[{"id":149800,"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/posts\/21433\/revisions\/149800"}],"wp:attachment":[{"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/media?parent=21433"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/categories?post=21433"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bananaip.com\/intellepedia\/wp-json\/wp\/v2\/tags?post=21433"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Methodology and Findings<\/h2>\n
Practical Applications<\/h2>\n
Disclaimer<\/h2>\n